Description

Usage

Arguments

x

- Number of success

n

- Number of trials from data

th0

- Hypothetical parameter for H0

a1

- Priors for hypothesis H1

b1

- Priors for hypothesis H1

Details

Computes Bayes factor under Beta-Binomial model for the
model: p = p0 Vs p not equal to p0 from the given number of
trials n and and for given number
of successes x = 0, 1, 2......n
We use the following guideline for reporting the results:

1/3 <= BaFa01 < 1: Evidence against H0 is not worth more than a bare mention.

1/20 <= BaFa01 < 1/3: Evidence against H0 is positive.

1/150 <= BaFa01 < 1/20: Evidence against H0 is strong.

BaFa10 < 1/150: Evidence against H0 is very strong.

1 <= BaFa01 < 3: Evidence against H1 is not worth more than a bare mention.

3 <= BaFa01 < 20: Evidence against H1 is positive.

20 <= BaFa01 < 150: Evidence against H1 is strong.

150 <= BaFa01: Evidence against H1 is very strong.

Value

A dataframe with

x

Number of successes

BaFa01

Bayesian Factor

References

[1] 2006 Ghosh M, Delampady M and Samanta T.
An introduction to Bayesian analysis: Theory and Methods.
Springer, New York